Voice communication devices such as cell phones, wireless phones and devices other than cell phones have become ubiquitous; they show up in almost every environment. These systems and devices and their associated communication methods are referred to by a variety of names, such as but not limited to, cellular telephones, cell phones, mobile phones, wireless telephones in the home and the office, and devices such as Personal Data Assistants (PDAs) that include a wireless or cellular telephone communication capability. They are used at home, office, inside a car, a train, at the airport, beach, restaurants and bars, on the street, and almost any other venue. As might be expected, these diverse environments have relatively higher and lower levels of background, ambient, or environmental noise. For example, there is generally less noise in a quiet home than there is in a crowded bar. If this noise, at sufficient levels, is picked up by the microphone, the intended voice communication degrades and though possibly not known to the users of the communication device, uses up more bandwidth or network capacity than is necessary, especially during non-speech segments in a two-way conversation when a user is not speaking.
In an on-going cell phone call or other communication from an environment having relatively higher environmental noise, it is sometimes difficult for the party at the other end of the conversation to hear what the party in the noisy environment is saying. That is, the ambient or environmental noise in the environment often “drowns out” the cell phone user's voice, whereby the other party cannot hear what is being said or even if they can hear it with sufficient volume the voice or speech is not understandable. This problem may even exist in spite of the conversation using a high data rate on the communication network.
The term “wind noise” is used to describe several different ways that wind can be generated. For example, wind can cause a loose shutter to bang against a house or it can cause a flag to rustle and snap. In these cases, the wind has caused an object to move, and the motion makes a sound. In other cases, wind moving past an object can create a howling sound, even though the object does not vibrate. Here, the sound is caused by turbulence that is created in the moving air as it passes by the object. This turbulence, which cannot be seen, is very similar to the turbulence in a fast-moving stream as the water flows around and over large rocks. We have all experienced this kind of wind noise while inside a house during a windstorm. The sound of the howling wind originates in the turbulence of air motion past the walls and roof.
The form of wind noise that most interferes with our ability to hear and communicate is the noise generated by air flow around our own head. Here the sound is generated within centimeters of our ears, and may be heard at quite a high level because of this close proximity [1]
It is known art to reduce wind noise by mechanical means. Such means alone, however, do not eliminate the wind noise to a satisfactory level.
Therefore, wind noise has been studied extensively and many solutions have been proposed for hearing aids, Bluetooth headsets etc.
Current wind noise reduction solutions use high-pass filters or subtract an estimate of the wind noise from the noisy signal. An efficient wind noise reduction can be achieved only if can be detected reliably and consistently.
Wind noise exhibits some properties and features that are common to other types of noise encountered in our daily lives. Depending on the wind speed, direction, physical obstructions like hats, caps, hand etc the characteristics of wind noise vary greatly. For these reasons, it is difficult to detect the presence of wind noise and cancel it when compared to other environmental noises.
However, certain factors make wind noise unique. Wind noise predominantly is a low-frequency phenomenon. Many of the known art technologies detect wind noise using the property of low correlation of the wind noise.
It is known art to reduce wind noise by mechanical means such as foam, scrims etc. To be sufficiently effective, the mechanical means must be thick which might make the device look bulky. This can be undesirable.
Several attempts to detect wind noise are known in the related art. US patent US2002/037088, assigned to Dickel et al, detects wind noise by computing the correlation between signals received at the two microphones. Turbulence created at the two microphones, without any obstructions, causes signals with low correlation. However, our studies showed that obstructions in the vicinity of the microphone result the correlation to be high.
European patent EP 1 339 256 A2, assigned to Roeck et al, uses several of the well know wind noise properties like high energy content at low frequencies, low auto-correlation at two microphones and high-magnitudes. However, this approach also suffers from the same drawbacks discussed above.
European patent application EP 1 732 352 A1, assigned to Hetherington et al, uses multiple microphones where power levels in different microphones are compared. When the power level of the sound received at the second microphone is less than the power level of the sound received at the first microphone by a predefined value, wind noise may be present. However, this approach requires one of the microphones to be directional with high directivity index and the other microphone to be Omni-directional with low directivity index.
U.S. Pat. No. 7,174,023 granted to Ozawa uses a multi-microphone approach. This approach uses passing the “difference signals” from multiple microphones through a low pass filter to extract wind noise for analysis and synthesis. However, our studies and recordings of wind noise under conditions show that wind noise is sometimes concentrated in higher frequency regions as well.
U.S. Pat. No. 5,288,955 granted to Staple et al talks about an arrangement in a bullet-shaped housing having a rounded front portion. However, this is a hardware approach.
US patent 2007/0003090 granted to Anderson talks about using a mesh made with either nylon or metal having a single or plurality of layers. This also is a hardware approach.
US patent US 2006/0120540 A1 granted to Luo uses one microphone and two microphones. The patent talks about hearing aids but it does not cover Bluetooth headsets and cell phones, where the introduction of the second microphone could sometimes be difficult.
Hence there is a need in the art for a method of wind noise reduction or cancellation that is robust, suitable for mobile use, and inexpensive to manufacture. The increased traffic in cellular telephone based communication systems has created a need in the art for means to provide a clear, high quality signal with a high signal-to-noise ratio.
It is an objective of the present invention to provide methods and devices that overcome disadvantages of prior art wind noise detection and reduction.
The requirements of a wind noise reduction system for speech enhancement are a) Intelligibility, naturalness of the enhanced signal, b) Improvement of the signal-to-noise ratio, c) Short signal delay and d) Computational simplicity
There are several methods for performing noise reduction, but all can be categorized as types of filtering. In the related art, speech and noise are mixed into one signal channel, where they reside in the same frequency band and may have similar correlation properties. Consequently, filtering will inevitably have an effect on both the speech signal and the background noise signal. Distinguishing between voice and background noise signals is a challenging task. Speech components may be perceived as noise components and may be suppressed or filtered along with the noise components.
It is an objective of the present invention to provide methods and devices that overcome disadvantages of prior art wind noise detection and reduction schemes. The methods should be computationally inexpensive, ability to detect and reduce low, medium and high levels of wind noise.